Handsfree Communication System and Method

ABSTRACT

A method, computer program product, and computing system for interfacing a clinical research system with a virtual assistant accessible by a clinical trial participant; providing a clinical research survey to the clinical trial participant via the virtual assistant, wherein the clinical research survey defines one or more questions; and receiving a survey response to the clinical research survey from the clinical trial participant via the virtual assistant, wherein the survey response defines one or more answers to the one or more questions defined within the clinical research survey.

RELATED APPLICATION(S)

This application claims the benefit of U.S. Provisional Application No.63/226,708, filed on 28 Jul. 2021, the entire contents of which areincorporated herein by reference.

TECHNICAL FIELD

This disclosure relates to communication systems and, more particularly,to communication systems that utilize virtual assistants within thebusiness space.

BACKGROUND

Handsfree communication is becoming very popular. Our cars allow us toverbally communicate with them and virtual assistants (e.g., Apple's Skiand Amazon's Alexa) allow us to obtain information in response to spokenrequests, as well as adjust thermostats, dim room lighting, change ourtelevision channels, etc.

Unfortunately, the manner in which voice control and virtual assistantshave been integrated into business application platforms is oftensuperficial at best. For example, such business application platformsoften only allow for voice control of simple cursory tasks . . . asopposed to more complex multi-step processes.

SUMMARY OF DISCLOSURE Hands Free, Voice-Based Survey Responses Via aSecure VA

In one implementation, a computer-implemented method is executed on acomputing device and includes: interfacing a clinical research systemwith a virtual assistant accessible by a clinical trial participant;providing a clinical research survey to the clinical trial participantvia the virtual assistant, wherein the clinical research survey definesone or more questions; and receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant, wherein the survey response defines one or more answers tothe one or more questions defined within the clinical research survey.

One or more of the following features may be included. Interfacing aclinical research system with a virtual assistant accessible by aclinical trial participant may include: enabling functionality on thevirtual assistant to effectuate cloud-based communication between thevirtual assistant and the clinical research system. Providing a clinicalresearch survey to the clinical trial participant via the virtualassistant may include: utilizing text-to-speech technology to generateone or more speech-based questions based, at least in part, upon the oneor more questions defined within the clinical research survey. Providinga clinical research survey to the clinical trial participant via thevirtual assistant may include: notifying the clinical trial participantof the availability of the clinical research survey. Providing aclinical research survey to the clinical trial participant via thevirtual assistant may include: confirming the identity of the clinicaltrial participant before enabling the clinical trial participant torespond to the clinical research survey. Providing a clinical researchsurvey to the clinical trial participant via the virtual assistant mayinclude: providing one or more speech-based questions based, at least inpart, upon the clinical research survey to the clinical trialparticipant so that the clinical trial participant may provide aspeech-based answer as part of the survey response. Receiving a surveyresponse to the clinical research survey from the clinical trialparticipant via the virtual assistant may include: processing at least aportion of the survey response using natural language processing.Receiving a survey response to the clinical research survey from theclinical trial participant via the virtual assistant may include:receiving one or more speech-based answers from the clinical trialparticipant as part of the survey response. Receiving a survey responseto the clinical research survey from the clinical trial participant viathe virtual assistant may include: generating one or more text-basedanswers from the one or more speech-based answers received from theclinical trial participant as part of the survey response. Receiving asurvey response to the clinical research survey from the clinical trialparticipant via the virtual assistant may include: associating the oneor more text-based answers with the one or more questions defined withinthe clinical research survey.

In another implementation, a computer program product resides on acomputer readable medium and has a plurality of instructions stored onit. When executed by a processor, the instructions cause the processorto perform operations including interfacing a clinical research systemwith a virtual assistant accessible by a clinical trial participant;providing a clinical research survey to the clinical trial participantvia the virtual assistant, wherein the clinical research survey definesone or more questions; and receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant, wherein the survey response defines one or more answers tothe one or more questions defined within the clinical research survey.

One or more of the following features may be included. Interfacing aclinical research system with a virtual assistant accessible by aclinical trial participant may include: enabling functionality on thevirtual assistant to effectuate cloud-based communication between thevirtual assistant and the clinical research system. Providing a clinicalresearch survey to the clinical trial participant via the virtualassistant may include: utilizing text-to-speech technology to generateone or more speech-based questions based, at least in part, upon the oneor more questions defined within the clinical research survey. Providinga clinical research survey to the clinical trial participant via thevirtual assistant may include: notifying the clinical trial participantof the availability of the clinical research survey. Providing aclinical research survey to the clinical trial participant via thevirtual assistant may include: confirming the identity of the clinicaltrial participant before enabling the clinical trial participant torespond to the clinical research survey. Providing a clinical researchsurvey to the clinical trial participant via the virtual assistant mayinclude: providing one or more speech-based questions based, at least inpart, upon the clinical research survey to the clinical trialparticipant so that the clinical trial participant may provide aspeech-based answer as part of the survey response. Receiving a surveyresponse to the clinical research survey from the clinical trialparticipant via the virtual assistant may include: processing at least aportion of the survey response using natural language processing.Receiving a survey response to the clinical research survey from theclinical trial participant via the virtual assistant may include:receiving one or more speech-based answers from the clinical trialparticipant as part of the survey response. Receiving a survey responseto the clinical research survey from the clinical trial participant viathe virtual assistant may include: generating one or more text-basedanswers from the one or more speech-based answers received from theclinical trial participant as part of the survey response. Receiving asurvey response to the clinical research survey from the clinical trialparticipant via the virtual assistant may include: associating the oneor more text-based answers with the one or more questions defined withinthe clinical research survey.

In another implementation, a computing system includes a processor and amemory system configured to perform operations including interfacing aclinical research system with a virtual assistant accessible by aclinical trial participant; providing a clinical research survey to theclinical trial participant via the virtual assistant, wherein theclinical research survey defines one or more questions; and receiving asurvey response to the clinical research survey from the clinical trialparticipant via the virtual assistant, wherein the survey responsedefines one or more answers to the one or more questions defined withinthe clinical research survey.

One or more of the following features may be included. Interfacing aclinical research system with a virtual assistant accessible by aclinical trial participant may include: enabling functionality on thevirtual assistant to effectuate cloud-based communication between thevirtual assistant and the clinical research system. Providing a clinicalresearch survey to the clinical trial participant via the virtualassistant may include: utilizing text-to-speech technology to generateone or more speech-based questions based, at least in part, upon the oneor more questions defined within the clinical research survey. Providinga clinical research survey to the clinical trial participant via thevirtual assistant may include: notifying the clinical trial participantof the availability of the clinical research survey. Providing aclinical research survey to the clinical trial participant via thevirtual assistant may include: confirming the identity of the clinicaltrial participant before enabling the clinical trial participant torespond to the clinical research survey. Providing a clinical researchsurvey to the clinical trial participant via the virtual assistant mayinclude: providing one or more speech-based questions based, at least inpart, upon the clinical research survey to the clinical trialparticipant so that the clinical trial participant may provide aspeech-based answer as part of the survey response. Receiving a surveyresponse to the clinical research survey from the clinical trialparticipant via the virtual assistant may include: processing at least aportion of the survey response using natural language processing.Receiving a survey response to the clinical research survey from theclinical trial participant via the virtual assistant may include:receiving one or more speech-based answers from the clinical trialparticipant as part of the survey response. Receiving a survey responseto the clinical research survey from the clinical trial participant viathe virtual assistant may include: generating one or more text-basedanswers from the one or more speech-based answers received from theclinical trial participant as part of the survey response. Receiving asurvey response to the clinical research survey from the clinical trialparticipant via the virtual assistant may include: associating the oneor more text-based answers with the one or more questions defined withinthe clinical research survey.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features andadvantages will become apparent from the description, the drawings, andthe claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic view of a distributed computing networkincluding a computing device that executes a communication processaccording to an embodiment of the present disclosure;

FIG. 2 is a flowchart of the communication process of FIG. 1 accordingto an embodiment of the present disclosure;

FIG. 3 is a flowchart of the communication process of FIG. 1 accordingto another embodiment of the present disclosure;

FIG. 4 is a diagrammatic view of a hospital room (including a hospitalbed and a television) according to an embodiment of the presentdisclosure;

FIG. 5 is a flowchart of the communication process of FIG. 1 accordingto another embodiment of the present disclosure;

FIG. 6 is a flowchart of the communication process of FIG. 1 accordingto another embodiment of the present disclosure;

FIG. 7 is a flowchart of the communication process of FIG. 1 accordingto another embodiment of the present disclosure;

FIG. 8 is a flowchart of the communication process of FIG. 1 accordingto another embodiment of the present disclosure;

FIG. 9 is a flowchart of the communication process of FIG. 1 accordingto another embodiment of the present disclosure; and

FIG. 10 is a flowchart of the communication process of FIG. 1 accordingto another embodiment of the present disclosure.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

System Overview

Referring to FIG. 1 , there is shown communication process 10.Communication process 10 may be implemented as a server-side process, aclient-side process, or a hybrid server-side/client-side process. Forexample, communication process 10 may be implemented as a purelyserver-side process via communication process 10 s. Alternatively,communication process 10 may be implemented as a purely client-sideprocess via one or more of communication process 10 c 1, communicationprocess 10 c 2, communication process 10 c 3, and communication process10 c 4. Alternatively still, communication process 10 may be implementedas a hybrid server-side/client-side process via communication process 10s in combination with one or more of communication process 10 c 1,communication process 10 c 2, communication process 10 c 3, andcommunication process 10 c 4. Accordingly, communication process 10 asused in this disclosure may include any combination of communicationprocess 10 s, communication process 10 c 1, communication process 10 c2, communication process 10 c 3, and communication process 10 c 4.

Communication process 10 s may be a server application and may reside onand may be executed by computing device 12, which may be connected tonetwork 14 (e.g., the Internet or a local area network). Examples ofcomputing device 12 may include, but are not limited to: a personalcomputer, a server computer, a series of server computers, a minicomputer, a mainframe computer, or a cloud-based computing platform.

The instruction sets and subroutines of communication process 10 s,which may be stored on storage device 16 coupled to computing device 12,may be executed by one or more processors (not shown) and one or morememory architectures (not shown) included within computing device 12.Examples of storage device 16 may include but are not limited to: a harddisk drive; a RAID device; a random-access memory (RAM); a read-onlymemory (ROM); and all forms of flash memory storage devices.

Network 14 may be connected to one or more secondary networks (e.g.,network 18), examples of which may include but are not limited to: alocal area network; a wide area network; or an intranet, for example.

Examples of communication processes 10 c 1, 10 c 2, 10 c 3, 10 c 4 mayinclude but are not limited to a web browser, a game console userinterface, a mobile device user interface, or a specialized application(e.g., an application running on e.g., the Android™ platform, the iOS™platform, the Windows™ platform, the Linux™ platform or the UNIXplatform). The instruction sets and subroutines of communicationprocesses 10 c 1, 10 c 2, 10 c 3, 10 c 4, which may be stored on storagedevices 20, 22, 24, 26 (respectively) coupled to client electronicdevices 28, 30, 32, 34 (respectively), may be executed by one or moreprocessors (not shown) and one or more memory architectures (not shown)incorporated into client electronic devices 28, 30, 32, 34(respectively). Examples of storage devices 20, 22, 24, 26 may includebut are not limited to: hard disk drives; RAID devices; random accessmemories (RAM); read-only memories (ROM), and all forms of flash memorystorage devices.

Examples of client electronic devices 28, 30, 32, 34 may include, butare not limited to, a smartphone (not shown), a personal digitalassistant (not shown), a tablet computer (not shown), laptop computers28, 30, virtual assistant 32, personal computer 34, a notebook computer(not shown), a server computer (not shown), a gaming console (notshown), and a dedicated network device (not shown). Client electronicdevices 28, 30, 32, 34 may each execute an operating system, examples ofwhich may include but are not limited to Microsoft Windows™, Android™,iOS™, Linux™, or a custom operating system.

Users 36, 38, 40, 42 may access communication process 10 directlythrough network 14 or through secondary network 18. Further,communication process 10 may be connected to network 14 throughsecondary network 18, as illustrated with link line 44.

The various client electronic devices (e.g., client electronic devices28, 30, 32, 34) may be directly or indirectly coupled to network 14 (ornetwork 18). For example, laptop computer 28 and laptop computer 30 areshown wirelessly coupled to network 14 via wireless communicationchannels 44, 46 (respectively) established between laptop computers 28,30 (respectively) and cellular network/bridge 48, which is showndirectly coupled to network 14. Further, virtual assistant 32 is shownwirelessly coupled to network 14 via wireless communication channel 50established between virtual assistant 32 and wireless access point(i.e., WAP 52), which is shown directly coupled to network 14.Additionally, personal computer 34 is shown directly coupled to network18 via a hardwired network connection.

WAP 52 may be, for example, an IEEE 802.11a, 802.11b, 802.11g, 802.11n,Wi-Fi, and/or Bluetooth device that is capable of establishing wirelesscommunication channel 50 between laptop computer 32 and WAP 52. As isknown in the art, IEEE 802.11x specifications may use Ethernet protocoland carrier sense multiple access with collision avoidance (i.e.,CSMA/CA) for path sharing. As is known in the art, Bluetooth is atelecommunications industry specification that allows e.g., mobilephones, computers, and personal digital assistants to be interconnectedusing a short-range wireless connection.

Communication Process Overview

As will be discussed below in greater detail, communication process 10may be configured to monitor the conversations between various entities(e.g., users, professionals, callers, patients) so that e.g.,professionals may be monitored and assistance may be rendered.

Automated Monitoring for Bias Detection

Referring also to FIG. 2 , communication process 10 may monitor 100 aconversation (e.g., conversation 54) between a professional (e.g., user40) and a third party (e.g., third party 56).

The conversation (e.g., conversation 54) between a professional (e.g.,user 40) and a third party (e.g., third party 56) may include one ormore of: an in-person conversation (e.g., conversation 54) between aprofessional (e.g., user 40) and a third party (e.g., third party 56); atelephone conversation (e.g., conversation 54) between a professional(e.g., user 40) and a third party (e.g., third party 56); and an AVconversation (e.g., conversation 54) between a professional (e.g., user40) and a third party (e.g., third party 56).

-   -   In-Person Conversation: Examples of such an in-person        conversation (e.g., conversation 54) may include but are not        limited to an in-person conversation (e.g., conversation 54)        between a medical professional (e.g., user 40) and a patient        (e.g., third party 56); an in-person conversation (e.g.,        conversation 54) between a supervisor (e.g., user 40) and an        employee (e.g., third party 56); and an in-person conversation        (e.g., conversation 54) between a help center employee (e.g.,        user 40) and a caller (e.g., third party 56).    -   Telephone Conversation: Examples of such a telephone        conversation (e.g., conversation 54) may include but are not        limited to a telephone conversation (e.g., conversation 54)        between a medical professional (e.g., user 40) and a patient        (e.g., third party 56); a telephone conversation (e.g.,        conversation 54) between a supervisor (e.g., user 40) and an        employee (e.g., third party 56); and a telephone conversation        (e.g., conversation 54) between a help center employee (e.g.,        user 40) and a caller (e.g., third party 56).    -   AV Conversation: Examples of such an AV conversation (e.g.,        conversation 54) may include but are not limited to an AV        conversation (e.g., conversation 54) between a medical        professional (e.g., user 40) and a patient (e.g., third party        56); an AV conversation (e.g., conversation 54) between a        supervisor (e.g., user 40) and an employee (e.g., third party        56); and an AV conversation (e.g., conversation 54) between a        help center employee (e.g., user 40) and a caller (e.g., third        party 56).

When monitoring 100 a conversation (e.g., conversation 54) between aprofessional (e.g., user 40) and a third party (e.g., third party 56),communication process 10 may monitor 102 a conversation (e.g.,conversation 54) between a professional (e.g., user 40) and a thirdparty (e.g., third party 56) using a virtual assistant (e.g., virtualassistant 32). Additionally/alternatively and when monitoring 100 aconversation (e.g., conversation 54) between a professional (e.g., user40) and a third party (e.g., third party 56), communication process 10may directly monitor the telephone conversation (e.g., conversation 54)between the professional (e.g., user 40) and the third party (e.g.,third party 56) and/or directly monitor the AV conversation (e.g.,conversation 54) between the professional (e.g., user 40) and a thirdparty (e.g., third party 56).

As is known in the art, a virtual assistant is a software agent that canperform tasks or services for an individual based on commands orquestions. The term “chatbot” is sometimes used to refer to virtualassistants generally or specifically accessed by online chat. In somecases, online chat programs are exclusively for entertainment purposes.Some virtual assistants are able to interpret human speech and respondvia synthesized voices. Users can ask their assistants questions,control home automation devices and media playback via voice, and manageother basic tasks such as email, to-do lists, and calendars withspeech-based commands. A similar concept, however with differences, laysunder the dialogue systems. As of 2017, the capabilities and usage ofvirtual assistants are expanding rapidly, with new products entering themarket and a strong emphasis on both email and voice user interfaces.Apple and Google have large installed bases of users on smartphones.Microsoft has a large installed base of Windows-based personalcomputers, smartphones and smart speakers. Amazon has a large installbase for smart speakers. Conversica has over 100 million engagements viaits email and SMS interface intelligent virtual assistants for business.

Communication process 10 may process 104 at least a portion of theconversation (e.g., conversation 54) to identify at least one instanceof bias, wherein the at least one instance of bias may include but isnot limited to one or more of: at least one instance of racial bias(i.e., treating people differently based upon their race); at least oneinstance of gender bias (i.e., treating people differently based upontheir gender); at least one instance of military status bias (i.e.,treating people differently based upon their military status); at leastone instance of disability bias (i.e., treating people differently basedupon their disabilities); and at least one instance of age bias (i.e.,treating people differently based upon their age). This above-describedinstances of bias are intended to be illustrative and not all inclusive.Accordingly, other instances of bias are possible and are considered tobe within the scope of this disclosure.

When processing 104 at least a portion of the conversation (e.g.,conversation 54) to identify at least one instance of bias,communication process 10 may process 106 at least a portion of theconversation (e.g., conversation 54) using natural language processing.As is known in the art, natural language processing is a subfield oflinguistics, computer science, and artificial intelligence concernedwith the interactions between computers and human language, inparticular how to program computers to process and analyze large amountsof natural language data. The goal is a computer capable of“understanding” the contents of documents, including the contextualnuances of the language within them. The technology can then accuratelyextract information and insights contained in the documents as well ascategorize and organize the documents themselves.

When processing 104 at least a portion of the conversation (e.g.,conversation 54) to identify at least one instance of bias,communication process 10 may also:

-   -   process 108 at least a portion of the conversation (e.g.,        conversation 54) to identify one or more bias-indicative trigger        words (e.g., “honey”, “darling”, “sweetie”, “old”, “aged”);    -   process 110 at least a portion of the conversation (e.g.,        conversation 54) to identify one or more bias-indicative        conversational structures (e.g., “people like you”, “where are        you from?”, “emotional types”); and    -   process 112 at least a portion of the conversation (e.g.,        conversation 54) to identify one or more bias-indicative vocal        tones/inflections (e.g., condescending tones/inflections,        sarcastic tones/inflections, derogatory tones/inflections).

The above-described bias-indicative trigger words, bias-indicativeconversational structures, and bias-indicative vocal tones/inflectionsmay be manually defined or may be automatically defined. For example, anadministrator of communication process 10 may manually define one ormore lists (e.g., lists 58) that identify such bias-indicative triggerwords, bias-indicative conversational structures, and bias-indicativevocal tones/inflections. Additionally/alternatively, an administrator ofcommunication process 10 may define seed data (e.g., seed data 60) thatmay be processed via artificial intelligence (AI) process 62 that may beconfigured to expand seed data 60 to define the above-referenced lists(e.g., lists 58).

As is known in the art, a machine learning system or model may generallyinclude an algorithm or combination of algorithms that has been trainedto recognize certain types of patterns. For example, machine learningapproaches may be generally divided into three categories, depending onthe nature of the signal available: supervised learning, unsupervisedlearning, and reinforcement learning. As is known in the art, supervisedlearning may include presenting a computing device with example inputsand their desired outputs, given by a “teacher”, where the goal is tolearn a general rule that maps inputs to outputs. With unsupervisedlearning, no labels are given to the learning algorithm, leaving it onits own to find structure in its input. Unsupervised learning can be agoal in itself (discovering hidden patterns in data) or a means towardsan end (feature learning). As is known in the art, reinforcementlearning may generally include a computing device interacting in adynamic environment in which it must perform a certain goal (such asdriving a vehicle or playing a game against an opponent). As itnavigates its problem space, the program is provided feedback that'sanalogous to rewards, which it tries to maximize. While three examplesof machine learning approaches have been provided, it will beappreciated that other machine learning approaches are possible withinthe scope of the present disclosure.

In order to harness greater processing power, when processing 104 atleast a portion of the conversation (e.g., conversation 54) to identifyat least one instance of bias, communication process 10 may process 114at least a portion of the conversation (e.g., conversation 54) on acloud-based computing resource (e.g., cloud resource 64) to identify atleast one instance of bias. As is known in the art, cloud computing isthe on-demand availability of computer system resources, especially datastorage (cloud storage) and computing power, without direct activemanagement by the user. Large clouds often have functions distributedover multiple locations, each location being a data center. Cloudcomputing relies on sharing of resources to achieve coherence andtypically using a “pay-as-you-go” model which can help in reducingcapital expenses but may also lead to unexpected operating expenses forunaware users.

If at least one instance of bias is detected, communication process 10may implement 116 at least one remedial task (e.g., task 66), whereinthese remedial tasks (e.g., task 66) may include one or more of:notifying management; encouraging supplemental training; requiringsupplemental training; and intervening in the conversation (e.g.,conversation 54).

-   -   Notifying Management: A supervisor (e.g., user 42) of user 40        (as well as user 40 themselves) may be notified by communication        process 10. Accordingly, the at least one instance of bias        identified by communication process 10 may be addressed more        discretely (by notifying user 40 only) or less discretely (by        notifying user 42).    -   Encouraging Supplemental Training: In less problematic        situations, user 40 may be asked/encouraged to attend some form        of supplemental training to address the at least one instance of        bias identified by communication process 10.    -   Requiring Supplemental Training: In more problematic situations,        user 40 may be required to attend some form of supplemental        training to address the at least one instance of bias identified        by communication process 10.    -   Intervening in the Conversation: In highly problematic        situations, communication process 10 may intervene in the        conversation (e.g., conversation 54) by e.g., looping in        management or terminating the conversation (e.g., conversation        54) to effectuate some form of damage control.

As would be expected, when implementing 116 at least one remedial task(e.g., task 66), communication process 10 may parse 118 the at least oneat least one remedial task (e.g., task 66) into a plurality of subtasks(e.g., subtasks 68), wherein communication process 10 may theneffectuate 120 the plurality of subtasks (e.g., subtasks 68). Forexample, in order to accomplish task 66, communication process 10 mayeffectuate a plurality of discrete subtasks (e.g., subtasks 68),examples of which may include but are not limited to contacting thesupervisor of user 40 and providing a private guidance message to user40.

Automated Monitoring for Suicide Prevention/Depression Detection

Referring also to FIG. 3 and as discussed above, communication process10 may monitor 100 a conversation (e.g., conversation 54) between aprofessional (e.g., user 40) and a third party (e.g., third party 56).

As also discussed above, the conversation (e.g., conversation 54)between a professional (e.g., user 40) and a third party (e.g., thirdparty 56) may include one or more of: an in-person conversation (e.g.,conversation 54) between a professional (e.g., user 40) and a thirdparty (e.g., third party 56); a telephone conversation (e.g.,conversation 54) between a professional (e.g., user 40) and a thirdparty (e.g., third party 56); and an AV conversation (e.g., conversation54) between a professional (e.g., user 40) and a third party (e.g.,third party 56).

-   -   In-Person Conversation: Examples of such an in-person        conversation (e.g., conversation 54) may include but are not        limited to an in-person conversation (e.g., conversation 54)        between a medical professional (e.g., user 40) and a patient        (e.g., third party 56); an in-person conversation (e.g.,        conversation 54) between a supervisor (e.g., user 40) and an        employee (e.g., third party 56); and an in-person conversation        (e.g., conversation 54) between a help center employee (e.g.,        user 40) and a caller (e.g., third party 56).    -   Telephone Conversation: Examples of such a telephone        conversation (e.g., conversation 54) may include but are not        limited to a telephone conversation (e.g., conversation 54)        between a medical professional (e.g., user 40) and a patient        (e.g., third party 56); a telephone conversation (e.g.,        conversation 54) between a supervisor (e.g., user 40) and an        employee (e.g., third party 56); and a telephone conversation        (e.g., conversation 54) between a help center employee (e.g.,        user 40) and a caller (e.g., third party 56).    -   AV Conversation: Examples of such an AV conversation (e.g.,        conversation 54) may include but are not limited to an AV        conversation (e.g., conversation 54) between a medical        professional (e.g., user 40) and a patient (e.g., third party        56); an AV conversation (e.g., conversation 54) between a        supervisor (e.g., user 40) and an employee (e.g., third party        56); and an AV conversation (e.g., conversation 54) between a        help center employee (e.g., user 40) and a caller (e.g., third        party 56).

Further and as discussed above, when monitoring 100 a conversation(e.g., conversation 54) between a professional (e.g., user 40) and athird party (e.g., third party 56), communication process 10 may monitor102 a conversation (e.g., conversation 54) between a professional (e.g.,user 40) and a third party (e.g., third party 56) using a virtualassistant (e.g., virtual assistant 32). Additionally/alternatively andwhen monitoring 100 a conversation (e.g., conversation 54) between aprofessional (e.g., user 40) and a third party (e.g., third party 56),communication process 10 may directly monitor the telephone conversation(e.g., conversation 54) between the professional (e.g., user 40) and thethird party (e.g., third party 56) and/or directly monitor the AVconversation (e.g., conversation 54) between the professional (e.g.,user 40) and a third party (e.g., third party 56).

Communication process 10 may process 200 at least a portion of theconversation (e.g., conversation 54) to identify at least one indicatorof depression, wherein the at least one indicator of depression mayinclude one or more of: an indicator of negative self-talk (e.g., anindicator that the third party 56 has a low opinion of themself and/ortalks about themself in a derogatory fashion); an indicator of apossibility of self-harm (e.g., an indicator that third party 56 mayhurt/harm themself); an indicator of a possibility of alcohol abuse(e.g., an indicator that third party 56 may abuse alcohol to cope withtheir situation); an indicator of a possibility of drug abuse (e.g., anindicator that third party 56 abuse drugs to cope with their situation);and an indicator of a possibility of suicide (e.g., an indicator thatthird party 56 may attempt to take their own life to cope with theirsituation). This above-described indicators of depression are intendedto be illustrative and not all inclusive. Accordingly, other indicatorof depression are possible and are considered to be within the scope ofthis disclosure

When processing 200 at least a portion of the conversation (e.g.,conversation 54) to identify at least one indicator of depression,communication process 10 may process 202 at least a portion of theconversation (e.g., conversation 54) using natural language processing.As discussed above, natural language processing is a subfield oflinguistics, computer science, and artificial intelligence concernedwith the interactions between computers and human language, inparticular how to program computers to process and analyze large amountsof natural language data. The goal is a computer capable of“understanding” the contents of documents, including the contextualnuances of the language within them. The technology can then accuratelyextract information and insights contained in the documents as well ascategorize and organize the documents themselves.

When processing 200 at least a portion of the conversation (e.g.,conversation 54) to identify at least one indicator of depression,communication process 10 may also:

-   -   process 204 at least a portion of the conversation (e.g.,        conversation 54) to identify one or more depression-indicative        trigger words (e.g., awful, hopeless, suicide, worthless);    -   process 206 at least a portion of the conversation (e.g.,        conversation 54) to identify one or more depression-indicative        conversational structures (e.g., “can't take it anymore”, “there        is nothing left”, “why bother”, “not worth it”; and/or    -   process 208 at least a portion of the conversation (e.g.,        conversation 54) to identify one or more depression-indicative        vocal tones/inflections (e.g., sad tones/inflections, hopeless        tones/inflections, derogatory tones/inflections).

The above-described depression-indicative trigger words,depression-indicative conversational structures, anddepression-indicative vocal tones/inflections may be manually defined ormay be automatically defined. For example, an administrator ofcommunication process 10 may manually define one or more lists (e.g.,lists 58) that identify such depression-indicative trigger words,depression-indicative conversational structures, anddepression-indicative vocal tones/inflections.Additionally/alternatively, an administrator of communication process 10may define seed data (e.g., seed data 60) that may be processed viaartificial intelligence (AI) process 62 that may be configured to expandseed data 60 to define the above-referenced lists (e.g., lists 58).

In order to harness greater processing power, when processing 200 atleast a portion of the conversation (e.g., conversation 54) to identifyat least one indicator of depression, communication process 10 mayprocess 210 at least a portion of the conversation (e.g., conversation54) on a cloud-based computing resource (e.g., cloud resource 64) toidentify at least one indicator of depression. As discussed above, cloudcomputing is the on-demand availability of computer system resources,especially data storage (cloud storage) and computing power, withoutdirect active management by the user. Large clouds often have functionsdistributed over multiple locations, each location being a data center.Cloud computing relies on sharing of resources to achieve coherence andtypically using a “pay-as-you-go” model which can help in reducingcapital expenses but may also lead to unexpected operating expenses forunaware users.

If at least one indicator of depression is detected, communicationprocess 10 may implement 212 at least one remedial task (e.g., task 66),wherein these remedial tasks (e.g., task 66) may include one or more of:notifying management; notifying emergency services; notifying lawenforcement; modifying the conversation (e.g., conversation 54); andintervening in the conversation (e.g., conversation 54).

-   -   Notifying Management: In less problematic situations, a        supervisor (e.g., user 42) of user 40 (as well as user 40        themselves) may be notified by communication process 10        concerning the indicator of depression detected with respect to        third party 56.    -   Notifying Emergency Services: In more problematic situations,        communication process 10 may notify emergency services to        address the indicator of depression detected with respect to        third party 56.    -   Notifying Law Enforcement: In more problematic situations,        communication process 10 may notify law enforcement to address        the indicator of depression detected with respect to third party        56.    -   Modifying the Conversation: In more problematic situations,        communication process 10 may modify the conversation (e.g., by        providing guidance to user 40) to steer the conversation into a        desired area.    -   Intervening in the Conversation: In highly problematic        situations, communication process 10 may intervene in the        conversation (e.g., conversation 54) by e.g., looping in        management to triage and/or gain control of the situation (as        well as notifying emergency services/law enforcement).

As discussed above, when implementing 212 at least one remedial task(e.g., task 66), communication process 10 may parse 214 the at least oneat least one remedial task (e.g., task 66) into a plurality of subtasks(e.g., subtasks 68), wherein communication process 10 may theneffectuate 216 the plurality of subtasks (e.g., subtasks 68). Forexample, in order to accomplish task 66, communication process 10 mayeffectuate a plurality of discrete subtasks (e.g., subtasks 68),examples of which may include but are not limited to contacting thesupervisor of user 40 and providing a private guidance message to user40.

Referring also to FIG. 4 and as will be discussed below in greaterdetail, communication process 10 may be configured to provide a newlevel of convenience and connectivity for patients when admitted to ahospital. Specifically, hospital rooms (e.g., hospital room 300)typically include a corded controller (not shown) that enables a patient(e.g., patient 302) within the hospital to e.g., contact the nurse'sstation, and control the hospital bed (e.g., hospital bed 304) and thetelevision (e.g., television 306). Unfortunately, this corded controller(not shown) is often difficult to locate and unsanitary to touch.

Hands Free, Voice-Based Interaction with Medical Staff in a Hospital

Referring also to FIG. 5 , communication process 10 may monitor 400 thediction of a patient (e.g., patient 302) within a hospital room (e.g.,hospital room 300). When monitoring 400 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300),communication process 10 may monitor 402 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300) using avirtual assistant (e.g., virtual assistant 32).

Additionally and when monitoring 400 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300),communication process 10 may monitor 404 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300) to listenfor the utterance of a wake-up word. Examples of such wake-up words mayinclude but are not limited to “Siri”, “Alexa”, “Google” and “Edera”.

Communication process 10 may process 406 at least a portion of thediction to identify at least one communication request within thehospital room (e.g., hospital room 300), wherein examples of suchcommunication requests within the hospital room (e.g., hospital room300) may include but are not limited to one or more of: placing afood/beverage order; requesting medication; contacting the nurse'sstation; and calling for emergency assistance.

-   -   Placing a Food/Beverage Order; For example, patient (e.g.,        patient 302) may order lunch by saying “Hey Edera, I would like        to order lunch”.    -   Requesting Medication; For example, patient (e.g., patient 302)        may request medication by saying “Hey Edera, can I please have        my pain medication”.    -   Contacting the Nurse's Station; For example, patient (e.g.,        patient 302) may request non-emergency assistance by saying “Hey        Edera, can I please have some assistance getting to the        bathroom”.    -   Calling for Emergency Assistance: For example, patient (e.g.,        patient 302) may request emergency assistance by saying “Hey        Edera, Help! I am having chest pains”.

When processing 406 at least a portion of the diction to identify atleast one communication request (e.g., placing a food/beverage order;requesting medication; contacting the nurse's station; and calling foremergency assistance) within the hospital room (e.g., hospital room300), communication process 10 may process at least a portion of thediction using natural language processing. As discussed above, naturallanguage processing is a subfield of linguistics, computer science, andartificial intelligence concerned with the interactions betweencomputers and human language, in particular how to program computers toprocess and analyze large amounts of natural language data. The goal isa computer capable of “understanding” the contents of documents,including the contextual nuances of the language within them. Thetechnology can then accurately extract information and insightscontained in the documents as well as categorize and organize thedocuments themselves.

In order to harness greater processing power, when processing 406 atleast a portion of the diction to identify at least one communicationrequest (e.g., placing a food/beverage order; requesting medication;contacting the nurse's station; and calling for emergency assistance)within the hospital room (e.g., hospital room 300), communicationprocess 10 may process 408 at least a portion of the diction on acloud-based computing resource (e.g., cloud resource 64) to identify atleast one communication request within the hospital room (e.g., hospitalroom 300). As discussed above, cloud computing is the on-demandavailability of computer system resources, especially data storage(cloud storage) and computing power, without direct active management bythe user. Large clouds often have functions distributed over multiplelocations, each location being a data center. Cloud computing relies onsharing of resources to achieve coherence and typically using a“pay-as-you-go” model which can help in reducing capital expenses butmay also lead to unexpected operating expenses for unaware users.

If at least one communication request (e.g., placing a food/beverageorder; requesting medication; contacting the nurse's station; andcalling for emergency assistance) is detected, communication process 10may establish 410 communication (e.g., via connection 308) between thehospital room (e.g., hospital room 300) and a remote location (e.g.,nurse's station 310) within the hospital (e.g., hospital 312).

In order to effectuate such communication with the remote location(e.g., nurse's station 310), communication process 10 may interface 412the virtual assistant (e.g., virtual assistant 32) with the remotelocation (e.g., nurse's station 310) within the hospital (e.g., hospital312).

When interfacing 412 the virtual assistant (e.g., virtual assistant 32)with the remote location (e.g., nurse's station 310) within the hospital(e.g., hospital 312), communication process 10 may enable 414functionality on the virtual assistant (e.g., virtual assistant 32) toeffectuate cloud-based communication (e.g., via connection 308) betweenthe virtual assistant (e.g., virtual assistant 32) and the remotelocation (e.g., nurse's station 310) within the hospital (e.g., hospital312). For example, one or more applications (e.g., application 314) maybe installed/executed on the virtual assistant (e.g., virtual assistant32) to enable communication with the remote location (e.g., nurse'sstation 310) via communication process 10.

Communication process 10 may process 416 at least a portion of thediction to identify at least one supplemental command to be performedwithin the hospital room (e.g., hospital room 300), wherein the at leastone supplemental command to be performed within the hospital room (e.g.,hospital room 300) may include but are not limited to one or more of:controlling a hospital bed (e.g., hospital bed 302); controlling a roomlighting system (e.g., lighting system 316); and controlling atelevision (e.g., television 306).

When processing 416 at least a portion of the diction to identify atleast one supplemental command (e.g., controlling a hospital bed;controlling a room lighting system; and controlling a television) to beperformed within the hospital room (e.g., hospital room 300),communication process 10 may process 418 at least a portion of thediction on a cloud-based computing resource (e.g., cloud resource 64) toidentify at least one supplemental command (e.g., controlling a hospitalbed; controlling a room lighting system; and controlling a television)to be performed within the hospital room (e.g., hospital room 300).

Enabling Hands Free, Voice-Based Control of a Hospital Bed

Referring also to FIG. 6 , communication process 10 may monitor 400 thediction of a patient (e.g., patient 302) within a hospital room (e.g.,hospital room 300). When monitoring 400 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300),communication process 10 may monitor 402 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300) using avirtual assistant (e.g., virtual assistant 32).

Additionally and when monitoring 400 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300),communication process 10 may monitor 500 the diction of a patient (e.g.,patient 302) within a hospital room (e.g., hospital room 300) to listenfor the utterance of a wake-up word. Examples of such wake-up words mayinclude but are not limited to “Siri”, “Alexa”, “Google” and “Edera”.

Communication process 10 may process 502 at least a portion of thediction to identify at least one bed-control-command to be performed ona hospital bed (e.g., hospital bed 304) within the hospital room (e.g.,hospital room 300), wherein examples of such bed-control-commands to beperformed on a hospital bed (e.g., hospital bed 304) within the hospitalroom (e.g., hospital room 300) may include but are not limited to one ormore of: a head raise/lower bed-control-command; a knee raise/lowerbed-control-command; a feet raise/lower bed-control-command; a bedraise/lower bed-control-command; a heater on/off bed-control-command;and a massager on/off bed-control-command.

-   -   Head Raise/Lower Bed-Control-Command: For example, patient        (e.g., patient 302) may say “Hey Edera, Please raise my head”.    -   Knee Raise/Lower Bed-Control-Command: For example, patient        (e.g., patient 302) may say “Hey Edera, Please lower my knees”.    -   Feet Raise/Lower Bed-Control-Command: For example, patient        (e.g., patient 302) may say “Hey Edera, Please raise my feet”.    -   Bed Raise/Lower Bed-Control-Command: For example, patient (e.g.,        patient 302) may say “Hey Edera, Please lift the bed”.    -   Heater On/Off Bed-Control-Command: For example, patient (e.g.,        patient 302) may say “Hey Edera, Please turn on my bed heater”.    -   Massager On/Off Bed-Control-Command: For example, patient (e.g.,        patient 302) may say “Hey Edera, Please turn on my bed        messager”.

In order to harness greater processing power, when processing 502 atleast a portion of the diction to identify at least onebed-control-command (e.g., a head raise/lower bed-control-command; aknee raise/lower bed-control-command; a feet raise/lowerbed-control-command; a bed raise/lower bed-control-command; a heateron/off bed-control-command; and a massager on/off bed-control-command)to be performed on a hospital bed (e.g., hospital bed 304) within thehospital room (e.g., hospital room 300), communication process 10 mayprocess 504 at least a portion of the diction on a cloud-based computingresource (e.g., cloud resource 64) to identify at least onebed-control-command (e.g., a head raise/lower bed-control-command; aknee raise/lower bed-control-command; a feet raise/lowerbed-control-command; a bed raise/lower bed-control-command; a heateron/off bed-control-command; and a massager on/off bed-control-command)to be performed on a hospital bed (e.g., hospital bed 304) within thehospital room (e.g., hospital room 300). As discussed above, cloudcomputing is the on-demand availability of computer system resources,especially data storage (cloud storage) and computing power, withoutdirect active management by the user. Large clouds often have functionsdistributed over multiple locations, each location being a data center.Cloud computing relies on sharing of resources to achieve coherence andtypically using a “pay-as-you-go” model which can help in reducingcapital expenses but may also lead to unexpected operating expenses forunaware users.

If at least one bed-control-command (e.g., a head raise/lowerbed-control-command; a knee raise/lower bed-control-command; a feetraise/lower bed-control-command; a bed raise/lower bed-control-command;a heater on/off bed-control-command; and a massager on/offbed-control-command) is detected, communication process 10 mayeffectuate 506 the at least one bed-control-command on the hospital bed(e.g., hospital bed 304) within the hospital room (e.g., hospital room300).

In order to effectuate such communication with the hospital bed (e.g.,hospital bed 304), communication process 10 may interface 508 thevirtual assistant (e.g., virtual assistant 32) with the hospital bed(e.g., hospital bed 304) within the hospital room (e.g., hospital room300).

When interfacing 508 the virtual assistant (e.g., virtual assistant 32)with the hospital bed (e.g., hospital bed 304) within the hospital room(e.g., hospital room 300), communication process 10 may enable 510functionality on the virtual assistant (e.g., virtual assistant 32) toeffectuate cloud-based communication between the virtual assistant(e.g., virtual assistant 32) and the hospital bed (e.g., hospital bed304) within the hospital room (e.g., hospital room 300). For example,one or more applications (e.g., application 314) may beinstalled/executed on the virtual assistant (e.g., virtual assistant 32)to enable communication with the hospital bed (e.g., hospital bed 304)via communication process 10.

Communication process 10 may process 512 at least a portion of thediction to identify at least one supplemental command to be performedwithin the hospital room (e.g., hospital room 300), wherein examples ofthe at least one supplemental command to be performed within thehospital room (e.g., hospital room 300) may include but are not limitedto one or more of: placing a food/beverage order; requesting medication;contacting the nurse's station (e.g., nurse's station 310); calling foremergency assistance; controlling a room lighting system (e.g., lightingsystem 316); and controlling a television (e.g., television 306).

When processing 512 at least a portion of the diction to identify atleast one supplemental command (e.g., placing a food/beverage order;requesting medication; contacting the nurse's station; calling foremergency assistance; controlling a room lighting system; andcontrolling a television) to be performed within the hospital room(e.g., hospital room 300), communication process 10 may process 514 atleast a portion of the diction on a cloud-based computing resource(e.g., cloud resource 64) to identify at least one supplemental command(e.g., placing a food/beverage order; requesting medication; contactingthe nurse's station; calling for emergency assistance; controlling aroom lighting system; and controlling a television) to be performedwithin the hospital room (e.g., hospital room 300).

While communication process 10 was discussed above as being utilized ina work environment and in a hospital environment, other configurationsare possible. For example and as will be discussed below in greaterdetail, communication process 10 may be configured to provide assistanceto users while they are in their homes.

Enabling Hands Free, Voice-Based Refills of Medications

Referring also to FIG. 7 , communication process 10 may monitor 600 thediction of a prescription recipient (e.g., user 40) using a virtualassistant (e.g., virtual assistant 32). For this example, user 40 may bea recipient of a prescription (e.g., blood pressure medication) that isutilized on a long-term basis and is therefore repeatedly and frequentlyrefilled.

Additionally and when monitoring 600 the diction of a prescriptionrecipient (e.g., user 40) using a virtual assistant (e.g., virtualassistant 32), communication process 10 may monitor 602 the diction of aprescription recipient (e.g., user 40) using a virtual assistant (e.g.,virtual assistant 32) to listen for the utterance of a wake-up word.Examples of such wake-up words may include but are not limited to “Ski”,“Alexa”, “Google” and “Edera”.

Communication process 10 may process 604 at least a portion of thediction to identify at least one prescription refill task (e.g., task66). One example of such a prescription refill task (e.g., task 66) maybe the prescription recipient (e.g., user 40) using the virtualassistant (e.g., virtual assistant 32) to ask to have their bloodpressure medication refilled.

When processing 604 at least a portion of the diction to identify atleast one prescription refill task (e.g., task 66), communicationprocess 10 may process 606 at least a portion of the diction usingnatural language processing. As discussed above, natural languageprocessing is a subfield of linguistics, computer science, andartificial intelligence concerned with the interactions betweencomputers and human language, in particular how to program computers toprocess and analyze large amounts of natural language data. The goal isa computer capable of “understanding” the contents of documents,including the contextual nuances of the language within them. Thetechnology can then accurately extract information and insightscontained in the documents as well as categorize and organize thedocuments themselves.

When processing 604 at least a portion of the diction to identify atleast one prescription refill task (e.g., task 66), communicationprocess 10 may also:

-   -   process 608 at least a portion of the diction to identify one or        more refill-indicative trigger words (e.g., “medicine”,        “prescription”, “refill”); and    -   process 610 at least a portion of the diction to identify one or        more refill-indicative conversational structures (e.g., “can I        have this filled”, “I need more medicine?”, “please refill my        prescription”).

The above-described refill-indicative trigger words andrefill-indicative conversational structures may be manually defined ormay be automatically defined. For example, an administrator ofcommunication process 10 may manually define one or more lists (e.g.,lists 58) that identify such refill-indicative trigger words andrefill-indicative conversational structures. Additionally/alternatively,an administrator of communication process 10 may define seed data (e.g.,seed data 60) that may be processed via artificial intelligence (AI)process 62 that may be configured to expand seed data 60 to define theabove-referenced lists (e.g., lists 58).

In order to harness greater processing power, when processing 604 atleast a portion of the diction to identify at least one prescriptionrefill task (e.g., task 66), communication process 10 may process 612 atleast a portion of the diction on a cloud-based computing resource toidentify at least one prescription refill task (e.g., task 66). Asdiscussed above, cloud computing is the on-demand availability ofcomputer system resources, especially data storage (cloud storage) andcomputing power, without direct active management by the user. Largeclouds often have functions distributed over multiple locations, eachlocation being a data center. Cloud computing relies on sharing ofresources to achieve coherence and typically using a “pay-as-you-go”model which can help in reducing capital expenses but may also lead tounexpected operating expenses for unaware users

If at least one prescription refill task (e.g., task 66) is detected(e.g., user 40 asking to have their blood pressure medication refilled),communication process 10 may effectuate 606 the at least oneprescription refill task (e.g., task 66) on a medical management system(e.g., medical management system 70), wherein examples of medicalmanagement system 70 may include but are not limited to one or more of:a medical office management system; a medical office billing system; anda pharmacy management system.

-   -   Medical Office Management System: A medical office management        system may be configured to enable medical professionals to        manage a medical practice by e.g., scheduling appointments,        scheduling staff, maintaining patient databases, maintaining        patient electronic health records, issuing prescriptions, etc.    -   Medical Office Billing System: A medical office billing system        may be configured to enable medical professionals to manage        accounts (e.g., account receivables and account payables) within        a medical practice by e.g., enabling monetary inflows into the        medical practice and enabling monetary outflows out of the        medical practice.    -   Pharmacy Management System: A pharmacy management system may be        configured to enable pharmaceutical professionals to manage a        pharmaceutical practice by e.g., processing prescriptions,        ordering inventory, scheduling staff, maintaining client        databases, maintaining client electronic pharmaceutical records,        etc.

Accordingly, and as used in this disclosure, medical management system(e.g., medical management system 70) may include a management systemand/or a billing system that is used in any type of medicalestablishment, example of which may include but are not limited to: adoctor's office, a medical practice, an urgent care facility, along-term care facility, a rehabilitation facility, a nursing facility,a hospice care facility, a hospital facility/organization, a lifesciences facility/organization, and a pharmacy facility/organization.

As will be discussed below, when effectuating 606 the at least oneprescription refill task (e.g., task 66) on a medical management system(e.g., a medical office management system, a medical office billingsystem or a pharmacy management system), communication process 10 mayparse 614 the at least one prescription refill task (e.g., task 66) intoa plurality of subtasks; and effectuate 616 the plurality of subtasks(e.g., subtasks 68) on the medical management system (e.g., a medicaloffice management system, a medical office billing system or a pharmacymanagement system).

For example and when effectuating 606 the at least one prescriptionrefill task (e.g., task 66) on a medical management system (e.g., amedical office management system, a medical office billing system or apharmacy management system), communication process 10 may identify 618which prescription medication(s) are currently refillable by theprescription recipient (e.g., user 40). For example, assume that theprescription refill task (e.g., task 66) issued by the prescriptionrecipient (e.g., user 40) was nonspecific (e.g., Please refill myprescription”) and the prescription recipient (e.g., user 40) iscurrently receiving three prescription medications (e.g., a bloodpressure medication, a cholesterol medication and an arthritismedication). Accordingly and when effectuating 606 the at least oneprescription refill task (e.g., task 66) on a medical management system(e.g., a medical office management system, a medical office billingsystem or a pharmacy management system), communication process 10 mayidentify 618 these three prescription medication(s) that are currentlyrefillable by the prescription recipient (e.g., user 40).

Further and when effectuating 606 the at least one prescription refilltask (e.g., task 66) on a medical management system (e.g., a medicaloffice management system, a medical office billing system or a pharmacymanagement system), communication process 10 may authenticate 620 theidentity of the prescription recipient (e.g., user 40); ask 622 theprescription recipient (e.g., user 40) to define the specific medicationto be refilled, thus defining a desired medication; and determine 624 ifthe desired medication is currently refillable. For example,communication process 10 may authenticate 620 the identity of theprescription recipient (e.g., user 40) using a voice print or via a PIN#/passcode; ask 622 the prescription recipient (e.g., user 40) to definethe specific medication to be refilled, thus defining a desiredmedication (e.g., by selecting the blood pressure medication of thethree medications that are refillable); and determine 624 if the desiredmedication is currently refillable (e.g., which may be determined byaccessing the medical office management system and/or the pharmacymanagement system).

As is known in the art, a voice print is a digital model of the uniquevocal characteristics of an individual. Voiceprints are created byspecialized computer programs which process speech samples. The creationof a voiceprint is often referred to as “enrollment” in a biometricsystem. There are two general approaches to the creation and use ofvoiceprints. In traditional voice biometric systems that use classicalmachine learning algorithms, a voiceprint is created by performing“feature extraction” on one or more speech samples. This featureextraction process essentially creates personalized calculations orvectors related to specific attributes that make the user's speechunique. In these systems, feature extraction is also used to create aUniversal Background Model or “UBM”.

Additionally and when effectuating 606 the at least one prescriptionrefill task (e.g., task 66) on a medical management system (e.g., amedical office management system, a medical office billing system or apharmacy management system): if the desired medication (e.g., the bloodpressure medication) is currently refillable, communication process 10may effectuate 626 the refilling of the desired medication (e.g., theblood pressure medication) via the pharmacy management system; andnotify 628 the prescription recipient (e.g., user 40) that the desiredmedication (e.g., the blood pressure medication) will be refilled.

Further and when effectuating 606 the at least one prescription refilltask (e.g., task 66) on a medical management system (e.g., a medicaloffice management system, a medical office billing system or a pharmacymanagement system): if the desired medication is not currentlyrefillable, communication process 10 may engage 630 the medicalmanagement system to determine if the desired medication (e.g., theblood pressure medication) may be refilled for the prescriptionrecipient (e.g., user 40). If the desired medication (e.g., the bloodpressure medication) may be refilled for the prescription recipient(e.g., user 40), communication process 10 may effectuate 632 therefilling of the desired medication (e.g., the blood pressuremedication) via a pharmacy management system and notify 634 theprescription recipient (e.g., user 40) that the desired medication(e.g., the blood pressure medication) will be refilled.

If the desired medication (e.g., the blood pressure medication) may notbe refilled for the prescription recipient (e.g., user 40),communication process 10 may notify 636 the prescription recipient(e.g., user 40) that the desired medication (e.g., the blood pressuremedication) will not be refilled.

As is known in the art, clinical research trials are utilized to gatherclinical information concerning e.g., new drugs/processes/devices thatare being tested in the marketplace. Unfortunately, one of the moredifficult parts of such clinical research trials is gathering suchclinical information from the trial participants. As will be discussedbelow in greater detail, communication process 10 may be configured toprovide assistance with respect to gathering such clinical informationfrom the trial participants.

Enabling Hands Free, Voice-Based Survey Responses via a Secure VA

Referring also to FIG. 8 , communication process 10 may interface 700 aclinical research system (e.g., clinical research system 72) with avirtual assistant (e.g., virtual assistant 32) accessible by a clinicaltrial participant (e.g., user 40). Examples of the clinical researchsystem (e.g., clinical research system 72) may include a system thatallows for the implementation of such clinical research trials and thegathering of such clinical information from the trial participants(e.g., user 40). For this example, assume that the trial participant(e.g., user 40) is involved in a clinical trial for the blood pressuremedication that that they are taking.

When interfacing 700 a clinical research system (e.g., clinical researchsystem 72) with a virtual assistant (e.g., virtual assistant 32)accessible by a clinical trial participant (e.g., user 40),communication process 10 may enable 702 functionality on the virtualassistant (e.g., virtual assistant 32) to effectuate cloud-basedcommunication between the virtual assistant (e.g., virtual assistant 32)and the clinical research system (e.g., clinical research system 72).For example, one or more applications (e.g., application 74) may beinstalled/executed on the virtual assistant (e.g., virtual assistant 32)to enable communication with the clinical research system (e.g.,clinical research system 72) via communication process 10.

Communication process 10 may provide 704 a clinical research survey(e.g., clinical research survey 76) to the clinical trial participant(e.g., user 40) via the virtual assistant (e.g., virtual assistant 32),wherein the clinical research survey (e.g., clinical research survey 76)may define one or more questions (e.g., questions 78). Examples of suchquestions (e.g., questions 78) may include questions concerning theefficacy of the blood pressure medication and the side effects of theblood pressure medication.

When providing 704 a clinical research survey (e.g., clinical researchsurvey 76) to the clinical trial participant (e.g., user 40) via thevirtual assistant (e.g., virtual assistant 32), communication process 10may utilize 706 text-to-speech technology to generate one or morespeech-based questions based, at least in part, upon the one or morequestions (e.g., questions 78) defined within the clinical researchsurvey (e.g., clinical research survey 76).

As is known in the art, a text-to-speech (TTS) system converts normallanguage text into speech and is composed of two parts: a front-end anda back-end. The front-end has two major tasks. First, it converts rawtext containing symbols like numbers and abbreviations into theequivalent of written-out words. This process is often called textnormalization, pre-processing, or tokenization. The front-end thenassigns phonetic transcriptions to each word, and divides and marks thetext into prosodic units, like phrases, clauses, and sentences. Theprocess of assigning phonetic transcriptions to words is calledtext-to-phoneme or grapheme-to-phoneme conversion. Phonetictranscriptions and prosody information together make up the symboliclinguistic representation that is output by the front-end. Theback-end—often referred to as the synthesizer—then converts the symboliclinguistic representation into sound. In certain systems, this partincludes the computation of the target prosody (pitch contour, phonemedurations), which is then imposed on the output speech.

When providing 704 a clinical research survey (e.g., clinical researchsurvey 76) to the clinical trial participant (e.g., user 40) via thevirtual assistant (e.g., virtual assistant 32), communication process 10may notify 708 the clinical trial participant (e.g., user 40) of theavailability of the clinical research survey (e.g., clinical researchsurvey 76). For example, communication process 10 may notify 708 theclinical trial participant (e.g., user 40) of the availability ofclinical research survey 76 by e.g., having virtual assistant 32 make aunique sound or flash a unique light. Additionally/alternatively,communication process 10 may notify 708 the clinical trial participant(e.g., user 40) of the availability of clinical research survey 76 bysending user 40 a text message or an email.

When providing 704 a clinical research survey (e.g., clinical researchsurvey 76) to the clinical trial participant (e.g., user 40) via thevirtual assistant (e.g., virtual assistant 32), communication process 10may confirm 710 the identity of the clinical trial participant (e.g.,user 40) before enabling the clinical trial participant (e.g., user 40)to respond to the clinical research survey (e.g., clinical researchsurvey 76). For example, communication process 10 may confirm 710 theidentity of the clinical trial participant (e.g., user 40) using a voiceprint or via a PIN #/passcode.

As discussed above, a voice print is a digital model of the unique vocalcharacteristics of an individual. Voiceprints are created by specializedcomputer programs which process speech samples. The creation of avoiceprint is often referred to as “enrollment” in a biometric system.There are two general approaches to the creation and use of voiceprints.In traditional voice biometric systems that use classical machinelearning algorithms, a voiceprint is created by performing “featureextraction” on one or more speech samples. This feature extractionprocess essentially creates personalized calculations or vectors relatedto specific attributes that make the user's speech unique. In thesesystems, feature extraction is also used to create a UniversalBackground Model or “UBM”.

When providing 704 a clinical research survey (e.g., clinical researchsurvey 76) to the clinical trial participant (e.g., user 40) via thevirtual assistant (e.g., virtual assistant 32), communication process 10may provide 712 one or more speech-based questions based, at least inpart, upon the clinical research survey (e.g., clinical research survey76) to the clinical trial participant (e.g., user 40) so that theclinical trial participant (e.g., user 40) may provide a speech-basedanswer as part of the survey response. For example, clinical researchsurvey 76 may include a plurality of text-based questions (e.g.,questions 78), wherein communication process 10 may utilizetext-to-speech technology to generate speech-based questions from thesetext-based questions. Communication process 10 may then provide 712these speech-based questions to the clinical trial participant (e.g.,user 40) so that the clinical trial participant (e.g., user 40) mayprovide a speech-based answer as part of a survey response (e.g., surveyresponse 80).

Additionally/alternatively, the virtual assistant (e.g., virtualassistant 32) may include a display screen (not shown) that allows forthe displaying of text & images. An example of such a virtual assistantmay include but is not limited to an Amazon Show™ device. Accordinglyand in such a configuration, when providing 704 a clinical researchsurvey (e.g., clinical research survey 76) to the clinical trialparticipant (e.g., user 40) via the virtual assistant (e.g., virtualassistant 32), communication process 10 may render one or moretext-based questions on the display screen (not shown) of the virtualassistant (e.g., virtual assistant 32), wherein these one or moretext-based questions may be based, at least in part, upon the one ormore questions (e.g., questions 78) defined within the clinical researchsurvey (e.g., clinical research survey 76).

Communication process 10 may receive 714 the survey response (e.g.,survey response 80) to the clinical research survey (e.g., clinicalresearch survey 76) from the clinical trial participant (e.g., user 40)via the virtual assistant (e.g., virtual assistant 32), wherein thesurvey response (e.g., survey response 80) defines one or more answers(e.g., answers 82) to the one or more questions (e.g., questions 78)defined within the clinical research survey (e.g., clinical researchsurvey 76).

When receiving 714 a survey response (e.g., survey response 80) to theclinical research survey (e.g., clinical research survey 76) from theclinical trial participant (e.g., user 40) via the virtual assistant(e.g., virtual assistant 32), communication process 10 may process 716at least a portion of the survey response (e.g., survey response 80)using natural language processing.

As discussed above, natural language processing is a subfield oflinguistics, computer science, and artificial intelligence concernedwith the interactions between computers and human language, inparticular how to program computers to process and analyze large amountsof natural language data. The goal is a computer capable of“understanding” the contents of documents, including the contextualnuances of the language within them. The technology can then accuratelyextract information and insights contained in the documents as well ascategorize and organize the documents themselves.

When receiving 714 a survey response (e.g., survey response 80) to theclinical research survey (e.g., clinical research survey 76) from theclinical trial participant (e.g., user 40) via the virtual assistant(e.g., virtual assistant 32), communication process 10 may receive 718one or more speech-based answers from the clinical trial participant(e.g., user 40) as part of the survey response (e.g., survey response80). For example, communication process 10 may provide the clinicaltrial participant (e.g., user 40) with speech-based questions that arebased upon the text-based questions (e.g., questions 78) included withinclinical research survey 76. The clinical trial participant (e.g., user40) may then provide speech-based answers as part of the survey response(e.g., survey response 80).

When receiving 714 a survey response (e.g., survey response 80) to theclinical research survey (e.g., clinical research survey 76) from theclinical trial participant (e.g., user 40) via the virtual assistant(e.g., virtual assistant 32), communication process 10 may generate 720one or more text-based answers (e.g., answers 82) from the one or morespeech-based answers received from the clinical trial participant (e.g.,user 40) as part of the survey response (e.g., survey response 80).

As is known in the art, speech recognition is an interdisciplinarysubfield of computer science and computational linguistics that developsmethodologies and technologies that enable the recognition andtranslation of spoken language into text by computers with the mainbenefit of searchability. It is also known as automatic speechrecognition (ASR), computer speech recognition or speech to text (STT).It incorporates knowledge and research in the computer science,linguistics and computer engineering fields. The reverse process isspeech synthesis. Some speech recognition systems require “training”(also called “enrollment”) where an individual speaker reads text orisolated vocabulary into the system. The system analyzes the person'sspecific voice and uses it to fine-tune the recognition of that person'sspeech, resulting in increased accuracy. Systems that do not usetraining are called “speaker-independent” systems. Systems that usetraining are called “speaker dependent”.

As discussed above, the virtual assistant (e.g., virtual assistant 32)may include a display screen (not shown) that allows for the displayingof text & images. An example of such a virtual assistant may include butis not limited to an Amazon Show™ device. Accordingly and in such aconfiguration, when receiving 714 a survey response (e.g., surveyresponse 80) to the clinical research survey (e.g., clinical researchsurvey 76) from the clinical trial participant (e.g., user 40) via thevirtual assistant (e.g., virtual assistant 32), communication process 10may enable the clinical trial participant (e.g., user 40) to type outresponses on the display screen (not shown) of the virtual assistant(e.g., virtual assistant 32).

Additionally, communication process 10 may require the clinical trialparticipant (e.g., user 40) to provide/upload information from apersonal medical device if required by the clinical research survey(e.g., clinical research survey 76). For example, if the clinicalresearch survey (e.g., clinical research survey 76) concerns theefficacy of a drug to control blood sugar, communication process 10 mayrequire the clinical trial participant (e.g., user 40) to uploadinformation from their personal blood glucose monitor.

When receiving 714 a survey response (e.g., survey response 80) to theclinical research survey (e.g., clinical research survey 76) from theclinical trial participant (e.g., user 40) via the virtual assistant(e.g., virtual assistant 32), communication process 10 may associate 722the one or more text-based answers (e.g., one or more of answers 82)with the one or more questions (e.g., questions 78) defined within theclinical research survey (e.g., clinical research survey 76).Accordingly, communication process 10 may e.g., associate 722 Answer #1(e.g., included within answers 82) with Question #1 (e.g., includedwithin questions 78), and may associate 722 Answer #2 (e.g., includedwithin answers 82) with Question #2 (e.g., included within questions78), and so on.

As will be discussed below in greater detail, communication process 10may be configure to allow for the utilization of a generic virtualassistant (e.g., virtual assistant 32) by a medical management system(e.g., medical management system 70) to automate the processing ofredundant and/or time-consuming tasks.

Using a Generic VA to Interface with Medical Office/Pharmacy ManagementSoftware

Referring also to FIG. 9 , communication process 10 may interface 800 ageneric virtual assistant (e.g., virtual assistant 32) with a medicalmanagement system (e.g., medical management system 70), wherein examplesof medical management system 70 may include but are not limited to oneor more of: a medical office management system; a medical office billingsystem; and a pharmacy management system

-   -   Medical Office Management System: A medical office management        system may be configured to enable medical professionals to        manage a medical practice by e.g., scheduling appointments,        scheduling staff, maintaining patient databases, maintaining        patient electronic health records, issuing prescriptions, etc.    -   Medical Office Billing System: A medical office billing system        may be configured to enable medical professionals to manage        accounts (e.g., account receivables and account payables) within        a medical practice by e.g., enabling monetary inflows into the        medical practice and enabling monetary outflows out of the        medical practice.    -   Pharmacy Management System: A pharmacy management system may be        configured to enable pharmaceutical professionals to manage a        pharmaceutical practice by e.g., processing prescriptions,        ordering inventory, scheduling staff, maintaining client        databases, maintaining client electronic pharmaceutical records,        etc.

As discussed above, medical management system (e.g., medical managementsystem 70) may include a management system and/or a billing system thatis used in any type of medical establishment, example of which mayinclude but are not limited to: a doctor's office, a medical practice,an urgent care facility, a long-term care facility, a rehabilitationfacility, a nursing facility, a hospice care facility, a hospitalfacility/organization, a life sciences facility/organization, and apharmacy facility/organization.

When interfacing 800 a generic virtual assistant (e.g., virtualassistant 32) with a medical management system (e.g., medical managementsystem 70), communication process 10 may enable 802 functionality on thegeneric virtual assistant (e.g., virtual assistant 32) to effectuatecloud-based communication between the generic virtual assistant (e.g.,virtual assistant 32) and the medical management system (e.g., medicalmanagement system 70). For example, one or more applications (e.g.,application 74) may be installed/executed on the virtual assistant(e.g., virtual assistant 32) to enable communication with the medicalmanagement system (e.g., medical management system 70) via communicationprocess 10.

Communication process 10 may monitor 804 the diction of a medicalspecialist (e.g., user 40) using the generic virtual assistant (e.g.,virtual assistant 32). For example and when monitoring 804 the dictionof a medical specialist (e.g., user 40) using the generic virtualassistant (e.g., virtual assistant 32), communication process 10 maymonitor 806 the diction of the medical specialist (e.g., user 40) usingthe generic virtual assistant (e.g., virtual assistant 32) to listen forthe utterance of a wake-up word. Examples of such wake-up words mayinclude but are not limited to “Ski”, “Alexa”, “Google” and “Edera”.

The medical specialist (e.g., user 40) utilizing the generic virtualassistant (e.g., virtual assistant 32) may be one of many differentprofessionals that work in the medical field. Accordingly and whenmonitoring 804 the diction of a medical specialist (e.g., user 40) usingthe generic virtual assistant (e.g., virtual assistant 32),communication process 10 may include one or more of the following:

-   -   monitor 804 the diction of a claim processing specialist (e.g.,        user 40) using the generic virtual assistant (e.g., virtual        assistant 32), wherein a claim processing specialist may e.g.,        process insurance claims within a medical office for submission        to insurance companies. For example, a claim processing        specialist may say “Hey Edera, please submit a claim to        Insurance Company X for a CAT Scan for Patient Mary Jones”.    -   monitor 804 the diction of a billing specialist (e.g., user 40)        using the generic virtual assistant (e.g., virtual assistant        32), wherein a billing specialist may e.g., process account        payable invoices to effectuate billing and process account        receivable invoices to effectuate payment. For example, a        billing specialist may say “Hey Edera, please generate and        submit an invoice to Patient Mary Jones for a $100 CAT Scan        copay”.    -   monitor 804 the diction of a data processing specialist (e.g.,        user 40) using the generic virtual assistant (e.g., virtual        assistant 32), wherein a data processing specialist may e.g.,        generate & update data records. For example, a data processing        specialist may say “Hey Edera, please update the contact phone        number for Patient Mary Jones to 123-456-7890”.    -   monitor 804 the diction of an ordering specialist (e.g., user        40) using the generic virtual assistant (e.g., virtual assistant        32), wherein an ordering specialist may e.g., effectuate the        ordering of supplies and the ordering of medical procedures. For        example, a data processing specialist may say “Hey Edera, please        order a CAT Scan for Patient Mary Jones”.

Communication process 10 may process 808 at least a portion of thediction to identify at least one task (e.g., task 66) to be performedwithin a medical management system (e.g., medical management system 70);and if at least one task (e.g., task 66) is detected, communicationprocess 10 may effectuate 810 the at least one task (e.g., task 66) onthe medical management system (e.g., medical management system 70).

When processing 808 at least a portion of the diction to identify atleast one task (e.g., task 66) to be performed within a medicalmanagement system (e.g., medical management system 70), communicationprocess 10 may process 812 at least a portion of the diction usingnatural language processing. As discussed above, natural languageprocessing is a subfield of linguistics, computer science, andartificial intelligence concerned with the interactions betweencomputers and human language, in particular how to program computers toprocess and analyze large amounts of natural language data. The goal isa computer capable of “understanding” the contents of documents,including the contextual nuances of the language within them. Thetechnology can then accurately extract information and insightscontained in the documents as well as categorize and organize thedocuments themselves.

When processing 808 at least a portion of the diction to identify atleast one task (e.g., task 66) to be performed within a medicalmanagement system (e.g., medical management system 70), communicationprocess 10 may also:

-   -   process 814 at least a portion of the diction to identify one or        more task-indicative trigger words (e.g., “submit”, “claim”,        “generate”, “update”, “order”); and    -   process 816 at least a portion of the diction to identify one or        more task-indicative conversational structures (e.g., “please        bill”, “I need to update”, “submit this invoice”).

The above-described task-indicative trigger words, and task-indicativeconversational structures may be manually defined or may beautomatically defined. For example, an administrator of communicationprocess 10 may manually define one or more lists (e.g., lists 58) thatidentify such task-indicative trigger words, and task-indicativeconversational structures. Additionally/alternatively, an administratorof communication process 10 may define seed data (e.g., seed data 60)that may be processed via artificial intelligence (AI) process 62 thatmay be configured to expand seed data 60 to define the above-referencedlists (e.g., lists 58).

When processing 808 at least a portion of the diction to identify atleast one task (e.g., task 66) to be performed within a medicalmanagement system (e.g., medical management system 70), communicationprocess 10 may process 818 at least a portion of the diction on acloud-based computing resource (e.g., cloud resource 64) to identify atleast one task (e.g., task 66) to be performed within a medicalmanagement system (e.g., medical management system 70). As is known inthe art, cloud computing is the on-demand availability of computersystem resources, especially data storage (cloud storage) and computingpower, without direct active management by the user. Large clouds oftenhave functions distributed over multiple locations, each location beinga data center. Cloud computing relies on sharing of resources to achievecoherence and typically using a “pay-as-you-go” model which can help inreducing capital expenses but may also lead to unexpected operatingexpenses for unaware users.

When effectuating 810 the at least one task (e.g., task 66) on themedical management system (e.g., medical management system 70),communication process 10 may parse 820 the at least one task (e.g., task66) into a plurality of subtasks (e.g., subtasks 68); and effectuate 822the plurality of subtasks (e.g., subtasks 68) on the medical managementsystem (e.g., medical management system 70). For example, in order toaccomplish task 66, communication process 10 may effectuate a pluralityof discrete subtasks (e.g., subtasks 68), examples of which may includebut are not limited to identifying any outstanding balance owed byPatient Mary Jones, incrementing that amount by a $100 copay for theordered CAT Scan, generating an invoice for that incremented amount, andsubmitting that invoice to Patient Mary Jones.

Further and when effectuating 810 the at least one task (e.g., task 66)on the medical management system (e.g., medical management system 70):communication process 10 may access 824 the medical management system(e.g., medical management system 70) using an application programinterface (e.g., API 84) of the medical management system (e.g., medicalmanagement system 70) to effectuate the at least one task (e.g., task66) on the medical management system (e.g., medical management system70).

As is known in the art, an application programming interface (API) is away for two or more computer programs to communicate with each other. Itis a type of software interface, offering a service to other pieces ofsoftware. A document or standard that describes how to build or use sucha connection or interface is called an API specification. A computersystem that meets this standard is said to implement or expose an API.The term API may refer either to the specification or to theimplementation.

Additionally/alternatively and when effectuating 810 the at least onetask (e.g., task 66) on the medical management system (e.g., medicalmanagement system 70): communication process 10 may commandeer 826 alocal user interface (e.g., user interface 86), normally used by themedical specialist (e.g., user 40), of the medical management system(e.g., medical management system 70) to effectuate the at least one taskon the medical management system (e.g., medical management system 70).Accordingly and is such a situation, when communication process 10 iseffectuating 810 the at least one task (e.g., task 66) on the medicalmanagement system (e.g., medical management system 70), the medicalspecialist (e.g., user 40) may watch what appears to be remotemanipulation of their local user interface (e.g., user interface 86)that they use to access the medical management system (e.g., medicalmanagement system 70).

Enabling Hands Free, Voice-Based Automation of Tasks

Referring also to FIG. 10 , communication process 10 may monitor 900 thediction of a medical specialist (e.g., user 40) using a virtualassistant (e.g., virtual assistant 32). For example and when monitoring900 the diction of a medical specialist (e.g., user 40) using a virtualassistant (e.g., virtual assistant 32), communication process 10 maymonitor 902 the diction of a medical specialist (e.g., user 40) using avirtual assistant (e.g., virtual assistant 32) to listen for theutterance of a wake-up word. Examples of such wake-up words may includebut are not limited to “Siri”, “Alexa”, “Google” and “Edera”.

As discussed above, the medical specialist (e.g., user 40) utilizingcommunication process 10 may be one of many different professionals thatwork in the medical field. Accordingly and when monitoring 900 thediction of a medical specialist (e.g., user 40) using the virtualassistant (e.g., virtual assistant 32), communication process 10 mayinclude one or more of the following:

-   -   monitor 900 the diction of a claim processing specialist (e.g.,        user 40) using the virtual assistant (e.g., virtual assistant        32), wherein a claim processing specialist may e.g., process        insurance claims within a medical office for submission to        insurance companies. For example, a claim processing specialist        may say “Hey Edera, please submit a claim to Insurance Company X        for a CAT Scan for Patient Mary Jones”.    -   monitor 900 the diction of a billing specialist (e.g., user 40)        using the virtual assistant (e.g., virtual assistant 32),        wherein a billing specialist may e.g., process account payable        invoices to effectuate billing and process account receivable        invoices to effectuate payment. For example, a billing        specialist may say “Hey Edera, please generate and submit an        invoice to Patient Mary Jones for a $100 CAT Scan copay”.    -   monitor 900 the diction of a data processing specialist (e.g.,        user 40) using the virtual assistant (e.g., virtual assistant        32), wherein a data processing specialist may e.g., generate &        update data records. For example, a data processing specialist        may say “Hey Edera, please update the contact phone number for        Patient Mary Jones to 123-456-7890”    -   monitor 900 the diction of an ordering specialist (e.g., user        40) using the virtual assistant (e.g., virtual assistant 32),        wherein an ordering specialist may e.g., effectuate the ordering        of supplies and the ordering of medical procedures. For example,        a data processing specialist may say “Hey Edera, please order a        CAT Scan for Patient Mary Jones”.

The above-described list is intended to be illustrative and not allinclusive. Accordingly, other configurations are possible and areconsidered to be within the scope of this disclosure. Communicationprocess 10 may interface 904 the virtual assistant (e.g., virtualassistant 32) with the medical management system (e.g., medicalmanagement system 70). For example and when interfacing 904 the virtualassistant (e.g., virtual assistant 32) with a medical management system(e.g., medical management system 70), communication process 10 mayenable 906 functionality on the virtual assistant (e.g., virtualassistant 32) to effectuate cloud-based communication between thevirtual assistant (e.g., virtual assistant 32) and the medicalmanagement system (e.g., medical management system 70). For example, oneor more applications (e.g., application 74) may be installed/executed onthe virtual assistant (e.g., virtual assistant 32) to enablecommunication with the medical management system (e.g., medicalmanagement system 70) via communication process 10.

Communication process 10 may process 908 at least a portion of thediction to identify at least one task (e.g., task 66) to be performedwithin a medical management system (e.g., medical management system 70),wherein examples of medical management system 70 may include but are notlimited to one or more of: a medical office management system; a medicaloffice billing system; and a pharmacy management system.

-   -   Medical Office Management System: A medical office management        system may be configured to enable medical professionals to        manage a medical practice by e.g., scheduling appointments,        scheduling staff, maintaining patient databases, maintaining        patient electronic health records, issuing prescriptions, etc.    -   Medical Office Billing System: A medical office billing system        may be configured to enable medical professionals to manage        accounts (e.g., account receivables and account payables) within        a medical practice by e.g., enabling monetary inflows into the        medical practice and enabling monetary outflows out of the        medical practice.    -   Pharmacy Management System: A pharmacy management system may be        configured to enable pharmaceutical professionals to manage a        pharmaceutical practice by e.g., processing prescriptions,        ordering inventory, scheduling staff, maintaining client        databases, maintaining client electronic pharmaceutical records,        etc.

As discussed above, medical management system (e.g., medical managementsystem 70) may include a management system and/or a billing system thatis used in any type of medical establishment, example of which mayinclude but are not limited to: a doctor's office, a medical practice,an urgent care facility, a long-term care facility, a rehabilitationfacility, a nursing facility, a hospice care facility, a hospitalfacility/organization, a life sciences facility/organization, and apharmacy facility/organization.

When processing 908 at least a portion of the diction to identify atleast one task (e.g., task 66) to be performed within a medicalmanagement system (e.g., medical management system 70), communicationprocess 10 may process 910 at least a portion of the diction usingnatural language processing. As discussed above, natural languageprocessing is a subfield of linguistics, computer science, andartificial intelligence concerned with the interactions betweencomputers and human language, in particular how to program computers toprocess and analyze large amounts of natural language data. The goal isa computer capable of “understanding” the contents of documents,including the contextual nuances of the language within them. Thetechnology can then accurately extract information and insightscontained in the documents as well as categorize and organize thedocuments themselves.

When processing 908 at least a portion of the diction to identify atleast one task (e.g., task 66) to be performed within a medicalmanagement system (e.g., medical management system 70), communicationprocess 10 may also:

-   -   process 912 at least a portion of the diction to identify one or        more task-indicative trigger words (e.g., “submit”, “claim”,        “generate”, “update”, “order”); and    -   process 914 at least a portion of the diction to identify one or        more task-indicative conversational structures (e.g., “please        bill”, “I need to update”, “submit this invoice”).

The above-described task-indicative trigger words, and task-indicativeconversational structures may be manually defined or may beautomatically defined. For example, an administrator of communicationprocess 10 may manually define one or more lists (e.g., lists 58) thatidentify such task-indicative trigger words, and task-indicativeconversational structures. Additionally/alternatively, an administratorof communication process 10 may define seed data (e.g., seed data 60)that may be processed via artificial intelligence (AI) process 62 thatmay be configured to expand seed data 60 to define the above-referencedlists (e.g., lists 58).

When processing 908 at least a portion of the diction to identify atleast one task (e.g., task 66) to be performed within a medicalmanagement system (e.g., medical management system 70), communicationprocess 10 may process 916 at least a portion of the diction on acloud-based computing resource to identify at least one task (e.g., task66) to be performed within a medical management system (e.g., medicalmanagement system 70). As discussed above, cloud computing is theon-demand availability of computer system resources, especially datastorage (cloud storage) and computing power, without direct activemanagement by the user. Large clouds often have functions distributedover multiple locations, each location being a data center. Cloudcomputing relies on sharing of resources to achieve coherence andtypically using a “pay-as-you-go” model which can help in reducingcapital expenses but may also lead to unexpected operating expenses forunaware users.

If at least one task (e.g., task 66) is detected, communication process10 may effectuate 916 the at least one task (e.g., task 66) on themedical management system (e.g., medical management system 70).

When effectuating 916 the at least one task (e.g., task 66) on themedical management system (e.g., medical management system 70),communication process 10 may parse 918 the at least one task (e.g., task66) into a plurality of subtasks (e.g., subtasks 68); and effectuate 920the plurality of subtasks (e.g., subtasks 68) on the medical managementsystem (e.g., medical management system 70). For example, in order toaccomplish task 66, communication process 10 may effectuate a pluralityof discrete subtasks (e.g., subtasks 68), examples of which may includebut are not limited to identifying any outstanding balance owed byPatient Mary Jones, incrementing that amount by a $100 copay for theordered CAT Scan, generating an invoice for that incremented amount, andsubmitting that invoice to Patient Mary Jones.

Further and when effectuating 916 the at least one task (e.g., task 66)on the medical management system (e.g., medical management system 70):communication process 10 may access 922 the medical management system(e.g., medical management system 70) using an application programinterface (e.g., API 84) of the medical management system (e.g., medicalmanagement system 70) to effectuate the at least one task (e.g., task66) on the medical management system (e.g., medical management system70).

As is known in the art, an application programming interface (API) is away for two or more computer programs to communicate with each other. Itis a type of software interface, offering a service to other pieces ofsoftware. A document or standard that describes how to build or use sucha connection or interface is called an API specification. A computersystem that meets this standard is said to implement or expose an API.The term API may refer either to the specification or to theimplementation.

Additionally/alternatively and when effectuating 916 the at least onetask (e.g., task 66) on the medical management system (e.g., medicalmanagement system 70): communication process 10 may commandeer 924 alocal user interface (e.g., user interface 86), normally used by themedical specialist (e.g., user 40), of the medical management system(e.g., medical management system 70) to effectuate the at least one task(e.g., task 66) on the medical management system (e.g., medicalmanagement system 70). Accordingly and is such a situation, whencommunication process 10 is effectuating 916 the at least one task(e.g., task 66) on the medical management system (e.g., medicalmanagement system 70), the medical specialist (e.g., user 40) may watchwhat appears to be remote manipulation of their local user interface(e.g., user interface 86) that they use to access the medical managementsystem (e.g., medical management system 70).

General

As will be appreciated by one skilled in the art, the present disclosuremay be embodied as a method, a system, or a computer program product.Accordingly, the present disclosure may take the form of an entirelyhardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,the present disclosure may take the form of a computer program producton a computer-usable storage medium having computer-usable program codeembodied in the medium.

Any suitable computer usable or computer readable medium may beutilized. The computer-usable or computer-readable medium may be, forexample but not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus, device,or propagation medium. More specific examples (a non-exhaustive list) ofthe computer-readable medium may include the following: an electricalconnection having one or more wires, a portable computer diskette, ahard disk, a random access memory (RAM), a read-only memory (ROM), anerasable programmable read-only memory (EPROM or Flash memory), anoptical fiber, a portable compact disc read-only memory (CD-ROM), anoptical storage device, a transmission media such as those supportingthe Internet or an intranet, or a magnetic storage device. Thecomputer-usable or computer-readable medium may also be paper or anothersuitable medium upon which the program is printed, as the program can beelectronically captured, via, for instance, optical scanning of thepaper or other medium, then compiled, interpreted, or otherwiseprocessed in a suitable manner, if necessary, and then stored in acomputer memory. In the context of this document, a computer-usable orcomputer-readable medium may be any medium that can contain, store,communicate, propagate, or transport the program for use by or inconnection with the instruction execution system, apparatus, or device.The computer-usable medium may include a propagated data signal with thecomputer-usable program code embodied therewith, either in baseband oras part of a carrier wave. The computer usable program code may betransmitted using any appropriate medium, including but not limited tothe Internet, wireline, optical fiber cable, RF, etc.

Computer program code for carrying out operations of the presentdisclosure may be written in an object oriented programming languagesuch as Java, Smalltalk, C++ or the like. However, the computer programcode for carrying out operations of the present disclosure may also bewritten in conventional procedural programming languages, such as the“C” programming language or similar programming languages. The programcode may execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through a local area network/a widearea network/the Internet (e.g., network 14).

The present disclosure is described with reference to flowchartillustrations and/or block diagrams of methods, apparatus (systems) andcomputer program products according to embodiments of the disclosure. Itwill be understood that each block of the flowchart illustrations and/orblock diagrams, and combinations of blocks in the flowchartillustrations and/or block diagrams, may be implemented by computerprogram instructions. These computer program instructions may beprovided to a processor of a general purpose computer/special purposecomputer/other programmable data processing apparatus, such that theinstructions, which execute via the processor of the computer or otherprogrammable data processing apparatus, create means for implementingthe functions/acts specified in the flowchart and/or block diagram blockor blocks.

These computer program instructions may also be stored in acomputer-readable memory that may direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meanswhich implement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

The flowcharts and block diagrams in the figures may illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustrations,and combinations of blocks in the block diagrams and/or flowchartillustrations, may be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the disclosure.As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present disclosure has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the disclosure in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the disclosure. Theembodiment was chosen and described in order to best explain theprinciples of the disclosure and the practical application, and toenable others of ordinary skill in the art to understand the disclosurefor various embodiments with various modifications as are suited to theparticular use contemplated.

A number of implementations have been described. Having thus describedthe disclosure of the present application in detail and by reference toembodiments thereof, it will be apparent that modifications andvariations are possible without departing from the scope of thedisclosure defined in the appended claims.

What is claimed is:
 1. A computer-implemented method, executed on acomputing device, comprising: interfacing a clinical research systemwith a virtual assistant accessible by a clinical trial participant;providing a clinical research survey to the clinical trial participantvia the virtual assistant, wherein the clinical research survey definesone or more questions; and receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant, wherein the survey response defines one or more answers tothe one or more questions defined within the clinical research survey.2. The computer-implemented method of claim 1 wherein interfacing aclinical research system with a virtual assistant accessible by aclinical trial participant includes: enabling functionality on thevirtual assistant to effectuate cloud-based communication between thevirtual assistant and the clinical research system.
 3. Thecomputer-implemented method of claim 1 wherein providing a clinicalresearch survey to the clinical trial participant via the virtualassistant includes: utilizing text-to-speech technology to generate oneor more speech-based questions based, at least in part, upon the one ormore questions defined within the clinical research survey.
 4. Thecomputer-implemented method of claim 1 wherein providing a clinicalresearch survey to the clinical trial participant via the virtualassistant includes: notifying the clinical trial participant of theavailability of the clinical research survey.
 5. Thecomputer-implemented method of claim 1 wherein providing a clinicalresearch survey to the clinical trial participant via the virtualassistant includes: confirming the identity of the clinical trialparticipant before enabling the clinical trial participant to respond tothe clinical research survey.
 6. The computer-implemented method ofclaim 1 wherein providing a clinical research survey to the clinicaltrial participant via the virtual assistant includes: providing one ormore speech-based questions based, at least in part, upon the clinicalresearch survey to the clinical trial participant so that the clinicaltrial participant may provide a speech-based answer as part of thesurvey response.
 7. The computer-implemented method of claim 1 whereinreceiving a survey response to the clinical research survey from theclinical trial participant via the virtual assistant includes:processing at least a portion of the survey response using naturallanguage processing.
 8. The computer-implemented method of claim 1wherein receiving a survey response to the clinical research survey fromthe clinical trial participant via the virtual assistant includes:receiving one or more speech-based answers from the clinical trialparticipant as part of the survey response.
 9. The computer-implementedmethod of claim 8 wherein receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant includes: generating one or more text-based answers from theone or more speech-based answers received from the clinical trialparticipant as part of the survey response.
 10. The computer-implementedmethod of claim 8 wherein receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant includes: associating the one or more text-based answers withthe one or more questions defined within the clinical research survey.11. A computer program product residing on a computer readable mediumhaving a plurality of instructions stored thereon which, when executedby a processor, cause the processor to perform operations comprising:interfacing a clinical research system with a virtual assistantaccessible by a clinical trial participant; providing a clinicalresearch survey to the clinical trial participant via the virtualassistant, wherein the clinical research survey defines one or morequestions; and receiving a survey response to the clinical researchsurvey from the clinical trial participant via the virtual assistant,wherein the survey response defines one or more answers to the one ormore questions defined within the clinical research survey.
 12. Thecomputer program product of claim 11 wherein interfacing a clinicalresearch system with a virtual assistant accessible by a clinical trialparticipant includes: enabling functionality on the virtual assistant toeffectuate cloud-based communication between the virtual assistant andthe clinical research system.
 13. The computer program product of claim11 wherein providing a clinical research survey to the clinical trialparticipant via the virtual assistant includes: utilizing text-to-speechtechnology to generate one or more speech-based questions based, atleast in part, upon the one or more questions defined within theclinical research survey.
 14. The computer program product of claim 11wherein providing a clinical research survey to the clinical trialparticipant via the virtual assistant includes: notifying the clinicaltrial participant of the availability of the clinical research survey.15. The computer program product of claim 11 wherein providing aclinical research survey to the clinical trial participant via thevirtual assistant includes: confirming the identity of the clinicaltrial participant before enabling the clinical trial participant torespond to the clinical research survey.
 16. The computer programproduct of claim 11 wherein providing a clinical research survey to theclinical trial participant via the virtual assistant includes: providingone or more speech-based questions based, at least in part, upon theclinical research survey to the clinical trial participant so that theclinical trial participant may provide a speech-based answer as part ofthe survey response.
 17. The computer program product of claim 11wherein receiving a survey response to the clinical research survey fromthe clinical trial participant via the virtual assistant includes:processing at least a portion of the survey response using naturallanguage processing.
 18. The computer program product of claim 11wherein receiving a survey response to the clinical research survey fromthe clinical trial participant via the virtual assistant includes:receiving one or more speech-based answers from the clinical trialparticipant as part of the survey response.
 19. The computer programproduct of claim 18 wherein receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant includes: generating one or more text-based answers from theone or more speech-based answers received from the clinical trialparticipant as part of the survey response.
 20. The computer programproduct of claim 18 wherein receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant includes: associating the one or more text-based answers withthe one or more questions defined within the clinical research survey.21. A computing system including a processor and memory configured toperform operations comprising: interfacing a clinical research systemwith a virtual assistant accessible by a clinical trial participant;providing a clinical research survey to the clinical trial participantvia the virtual assistant, wherein the clinical research survey definesone or more questions; and receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant, wherein the survey response defines one or more answers tothe one or more questions defined within the clinical research survey.22. The computing system of claim 21 wherein interfacing a clinicalresearch system with a virtual assistant accessible by a clinical trialparticipant includes: enabling functionality on the virtual assistant toeffectuate cloud-based communication between the virtual assistant andthe clinical research system.
 23. The computing system of claim 21wherein providing a clinical research survey to the clinical trialparticipant via the virtual assistant includes: utilizing text-to-speechtechnology to generate one or more speech-based questions based, atleast in part, upon the one or more questions defined within theclinical research survey.
 24. The computing system of claim 21 whereinproviding a clinical research survey to the clinical trial participantvia the virtual assistant includes: notifying the clinical trialparticipant of the availability of the clinical research survey.
 25. Thecomputing system of claim 21 wherein providing a clinical researchsurvey to the clinical trial participant via the virtual assistantincludes: confirming the identity of the clinical trial participantbefore enabling the clinical trial participant to respond to theclinical research survey.
 26. The computing system of claim 21 whereinproviding a clinical research survey to the clinical trial participantvia the virtual assistant includes: providing one or more speech-basedquestions based, at least in part, upon the clinical research survey tothe clinical trial participant so that the clinical trial participantmay provide a speech-based answer as part of the survey response. 27.The computing system of claim 21 wherein receiving a survey response tothe clinical research survey from the clinical trial participant via thevirtual assistant includes: processing at least a portion of the surveyresponse using natural language processing.
 28. The computing system ofclaim 21 wherein receiving a survey response to the clinical researchsurvey from the clinical trial participant via the virtual assistantincludes: receiving one or more speech-based answers from the clinicaltrial participant as part of the survey response.
 29. The computingsystem of claim 28 wherein receiving a survey response to the clinicalresearch survey from the clinical trial participant via the virtualassistant includes: generating one or more text-based answers from theone or more speech-based answers received from the clinical trialparticipant as part of the survey response.
 30. The computing system ofclaim 28 wherein receiving a survey response to the clinical researchsurvey from the clinical trial participant via the virtual assistantincludes: associating the one or more text-based answers with the one ormore questions defined within the clinical research survey.